Factors influencing physical inactivity status among Chinese pregnant women: a cross-sectional study

doi:10.21203/rs.3.rs-1953097/v1

Background: Regular prenatal physical activity can bring about health benefits to both mother and fetus and can reduce the risk of various complications of pregnancy. However, little is known about whether pregnant women in China are meeting the current guidelines for prenatal physical activity. The aims of the study were to assess physical inactivity status and associated factors among pregnant women in Shanghai, China.

Methods: A cross-sectional study of 1636 pregnant women were registered and received routine prenatal care at a tertiary obstetrics and gynecology hospital in Shanghai, China between May 2021 and March 2022. Maternal sociodemographic characteristics and health information were obtained using structured questionnaires or from the medical records. Maternal physical inactivity status was assessed using the International Physical Activity Questionnaire-Short Form and subjected to descriptive analysis. Factors pertinent to physical inactivity were identified by binary logistic regression and are reported with adjusted odds ratios (ORs) and 95% confidence intervals (CIs). Physical inactivity was defined as a total energy expenditure of <600 metabolic equivalent (MET) min/week.

Results: In total, the prevalence of physical inactivity was 47.5%. Multivariate logistic regression identified a significant negative association of physical inactivity with personal monthly income (adjusted OR 0.648, 95% CI 0.505–0.831), engagement in regular exercise before pregnancy (adjusted OR 0.575, 95% CI 0.464–0.711) and in the second (adjusted OR 0.534, 95% CI 0.411–0.693) and third (adjusted OR 0.615, 95% CI 0.470–0.806) trimester of pregnancy. Women with nausea or vomiting during pregnancy were more likely to be physically inactive during pregnancy (adjusted OR 1.307, 95% CI 1.002–1.705).

Conclusion: Physical inactivity is highly prevalent among pregnant women in China, particularly those with a low income, those who do not engage in regular exercise before pregnancy, those in the first trimester, and those with nausea or vomiting during pregnancy. These women require help to overcome barriers to physical activity and to promote health.

physical activity

exercise

pregnancy

pregnant women

factors

Physical activity (PA) is defined as any bodily movement produced by skeletal muscles that requires energy expenditure, and is an essential element of a healthy lifestyle [1]. A growing body of evidence suggests that regular prenatal exercise has health benefits for both mother and fetus [2]. Maternal benefits of being active during pregnancy include control of gestational weight gain, less risk of gestational diabetes mellitus (GDM), improved cardiovascular function, relief of lumbar and pelvic pain, a shorter delivery time, less likelihood of cesarean section, and, to some extent, improved psychological well-being [3]. A randomized controlled trial that included 300 overweight or obese Chinese women with uncomplicated singleton pregnancies found that initiation of cycling exercise for at least 30 minutes three times per week during the first trimester of pregnancy significantly decreased the amount of gestational weight gain and the risk of GDM with no increase in the risk of preterm birth [4]. Prenatal exercise also has some benefits for the fetus; for example, facilitating neurological development and reducing the risk of obesity at birth and in early childhood [5].

Considering the physiological and psychological benefits of engaging in regular prenatal exercise, the guidelines published by the World Health Organization (WHO) [2], the American College of Obstetricians and Gynecologists (ACOG) [1], the Society of Obstetricians and Gynecologists of Canada (SOGC), the Canadian Society for Exercise Physiology (CSEP) [6], the Department of Health and Social Care, UK [7], and the Australian Government Department of Health [8] all recommend that at least 150 min of moderate PA per week during pregnancy should be maintained when there are no pregnancy-related contraindications or complications. However, pregnant women are often physically inactive, with many who were previously active choosing to become inactive during pregnancy [9]. Compared with the PA level before conception, the level of PA during pregnancy is expected to be much lower and take a relatively single form. Recent studies reported that the rate of physical inactivity among pregnant women ranged from 27.2–88.9% [10–14]. In Brazil, the researchers evaluated the PA level in 2,706 pregnant women with GDM in the second or third trimester using the International Physical Activity Questionnaire (IPAQ) and found that only 34.3% reached the recommended levels [13]. Studies in other countries have yielded similar results. Several studies have investigated PA in pregnant women in China and found that the proportion of women meeting the recommendations ranged from 11% in Tianjin [11] to 57.1% in Chengdu [15]. This wide variation in PA reflects differences in geographic region, local culture, and assessment methods. Lü et al. used 600 metabolic equivalent (MET) min/week as the cut-off value that defined adequate PA in 2,485 pregnant women in China and showed that only 32.7% of women in the first trimester and 55.3% of those in the second or third trimester engaged in an adequate amount of PA [16]. However, their study included light PA when calculating MET, making it different from the international guidelines. Therefore, the variable findings in these studies may reflect use of different measurement tools and non-standard evaluation methods.

Factors that affect PA in pregnant women are complex and include individual demographic, physiologic, psychologic, and lifestyle factors, as well as social support and environmental factors. Researchers have showed that pregnant women who are younger, less well educated, and unemployed and those with multiple children and a lower income are less likely to engage in an adequate amount of PA [11, 12, 17, 18]. Obstetric variables associated with PA in pregnancy include history of miscarriage, parity, and exercise and smoking status before pregnancy [19–21]. Even though there is no scientific evidence linking prenatal exercise with adverse outcomes, some obstetric caregivers and pregnant women continue to be skeptical about the safety of prenatal exercise.

Chinese families tend to comply with the traditional philosophy of protecting the fetus from miscarriage by advising pregnant women to rest as much as possible, particularly in the first trimester [22]. However, younger women often receive modern health care-based PA recommendations and have to balance conflicting concepts of rest and activity during pregnancy, which may result in more women actively engaged in walking rather than PA of moderate intensity [16]. There is still no PA guideline specifically for pregnant Chinese women, and little is known about the PA status of these women, especially in Shanghai, a modern metropolitan city in the east of China. Knowledge of factors that influence the willingness of pregnant women to engage in an adequate amount of exercise is important to inform future interventions that can improve levels of PA during pregnancy. Therefore, the aims of this study were to investigate PA levels among pregnant women in Shanghai and to identify factors that influence the prevalence of physical inactivity.

Study design and participants

The study had a cross-sectional design and included pregnant women who were registered for and received routine prenatal care in an obstetrics and gynecology facility at a specialist tertiary hospital in Shanghai, China between May 2021 and March 2022. Women were eligible to participate in the study if they were aged 18 years or older, able to read and understand questions, and able to provide written informed consent. Women with serious comorbidity (e.g., cardiovascular disease, anemia, or asthma), poor mental health status, or a physical disability were excluded.

Ethical approval

The study protocol was approved by our institutional ethics committee (approval number 202123). All study participants provided written informed consent after receiving a verbal and written explanation about the purpose of the study and its procedures and being informed that they could withdraw from the study at any time for any reason.

Sample size

The sample size was calculated using the formula [23] with a 95% confidence level, a precision level of 3%, and the prevalence of physical inactivity during pregnancy of 42.9% (p=0.429) as follows:

p=0.429, q=1-p=571, e=0.03, z=1.96

Added a further 10% to allow for no-response in a required sample size of at least 1046. Finally, 1636 pregnant women were enrolled in the study.

Measures

Main outcome

The International Physical Activity Questionnaire short form (IPAQ-SF) has been recommended as a cost-effective method for assessment of the PA level in the general population, including pregnant women, and to have moderate to high reliability (rw=0.59) and concurrent validity (rw=0.55) [24]. Different types of activity are assigned different MET values based on a standard reference [25]. One MET is equivalent to the energy expenditure of sitting 1 hour quietly [26]. There are seven items in the IPAQ-SF [25]，six of which are related to the frequency and duration of PA including walking (3.3 MET), moderate-intensity physical activities (4.0 MET) like, yoga, Tai Ji, bicycling at a regular pace and playing table tennis, and vigorous-intensity physical activities (8.0 MET) such as swimming, running, rope skipping and aerobics, etc. Total energy expenditure (TEE) was derived by summing MET scores from each activity multiplied by total weekly minutes.

Covariates and other measurements

Sociodemographic, behavioral, obstetric, and social support data were collected using a structured questionnaire that was developed in consultation with experts in the field and pilot tested in 10 respondents before the survey. The sociodemographic characteristics consisted of age, ethnicity, level of education, current employment status, personal monthly income, and pre-pregnancy body mass index (BMI), which was calculated as body weight divided by the square of height. Using the Chinese classification, women with a BMI <18.5 kg/m² are considered underweight, those with a BMI of 18.5–23.9 kg/m² as normal weight, those with a BMI of 24–27.9 kg/m² as overweight, and those with a BMI ≥28 kg/m² as obese [27]. The behavioral characteristics before pregnancy are briefly described below. Regular exercise before pregnancy was defined as having consciously engaged in walking, cycling, yoga, running, or other PA for at least 30 min/week in the preconception period [28]. Pre-pregnancy smoking was defined as daily or intermittent smoking and passive smoking was defined as breathing second-hand tobacco smoke for more than 15 minutes a day in the 3 months before conception. Alcohol consumption before pregnancy was defined as drinking at least half a bottle of beer, 40 mL of white wine, or 125 mL of red wine in a month. The obstetric parameters included history of spontaneous abortion, parity, stage of pregnancy, singleton pregnancy, nausea and vomiting during pregnancy, measures taken to prevent miscarriage, and GDM. Questions about social support, including from family, friends, and health care providers, were also covered in the questionnaire.

Prenatal sleep quality was measured using the Chinese version of the Pittsburgh Sleep Quality Index (PSQI), which is the most frequently used generic measure of sleep in the research and clinical settings and has strong reliability and validity [29]. The PSQI includes 19 self-rated questions, which are divided into seven domains, including subjective sleep quality, sleep latency, sleep duration, sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction. The score in each domain of the PSQI ranges from 0 to 3 and the total score ranges from 0 to 21. A total PSQI score of >5 indicates poor sleep quality and a total score ≤5 is regarded as good sleep quality [30].

Prenatal anxiety status was assessed using the Chinese version of the Self-rating Anxiety Scale, which contains 20 items and is scored by calculating the frequency of symptoms corresponding to anxiety in the past week. Each item is scored on a 4-point scale ranging from 1 to 4; the scores for the 20 items are then added to obtain a rough score, which is then multiplied by 1.25 and the integer component taken to derive the standard score. The cut-off score for this scale is 50 points; a score of 50–59 is classified as mild anxiety, 60–69 as moderate anxiety, and >70 as severe anxiety[31].

Prenatal symptoms of depression were measured by the Edinburgh Postnatal Depression Scale, which is considered to have acceptable reliability, validity and applicability as a screening tool for depression during pregnancy [32]. This scale contains 10 items, each of which is scored from 0 to 3, with higher scores indicating a higher likelihood of perinatal depression. In general, a cut-off score of 10 or higher is recommended for detection of potential depression in pregnant Asian women [33].

Statistical analysis

The characteristics of the participants are presented as descriptive statistics. Continuous variables are summarized as the mean ± standard deviation if normally distributed and as the median (interquartile range) if not. Categorical variables are shown as the frequency (percentage). The dependent variable in this study was physical inactivity, which was defined as total energy expenditure <600 MET min/week. A binary logistic regression model was used to identify factors associated with physical inactivity in pregnant women and control for potential confounding variables. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. The steps used to identify these factors were as follows. First, we used backward elimination to remove variables with a p-value >0.2. Second, considering maternal age, level of education, pre-pregnancy BMI, parity, and history of spontaneous abortions to be clinically relevant or related to the level of PA in previous studies [19, 20, 23], we also added these five variables into the model. Finally, maternal age, level of education, current employment status, personal monthly income, pre-pregnancy BMI, regular exercise before pregnancy, alcohol consumption before pregnancy, history of spontaneous abortions, parity, stage of pregnancy, nausea and vomiting during pregnancy, and prenatal sleep quality were entered as independent variables into the logistic regression model. All statistical analyses were performed using the SPSS software package (version 25.0; IBM Corp., Armonk, NY, USA). A p-value of <0.05 was considered statistically significant.

In total, 1636 women were enrolled in the study. Twenty-two of the women did not meet the inclusion criteria, 64 dropped out during the study period, and 35 returned invalid questionnaires (incomplete or with inconsistent responses), leaving data for 1515 participants for analysis.

Characteristics of the participants

Table 1 shows the sociodemographic, behavioral, obstetric and social support characteristics of the overall sample. The average age was 30.6 ± 3.7 years, and 18.1% of the women were overweight or obese according to the Chinese BMI classification. The socioeconomic status of the majority of the participants was good, with 75.7% having a personal monthly income of more than 10,000 yuan; 71.7% of the women were still working. More than half of the women (55.5%) undertook regular exercise before pregnancy. In total, 13.1% of the women reported tobacco exposure before pregnancy. Most of the women were nulliparous and 79.3% experienced severe nausea and vomiting during pregnancy. The questionnaires were completed by 668 women in the first trimester, 389 in the second trimester, and 458 in the third trimester. Poor prenatal sleep quality was a common complaint. Overall, the participants were well-educated with 92.8% having completed a college degree.

Table 1 Characteristics of the participants (n=1515).

Variables	Frequency
Age (years), n (%) ＜25 25-29 30-34 ≥35	60 (4.0) 560 (37.0) 673 (44.4) 222 (14.7)
Ethnicity, n (%) Han Minorities	1491 (98.4) 24 (1.6)
Level of education, n (%) High school or less College Professional or graduate	109 (7.2) 1002 (66.1) 404 (26.7)
Current employment status, n (%) Does not work On duty	428 (28.3) 1087 (71.7)
Personal monthly income, n (%)^a ＜¥10,000 ≥¥10,000	368 (24.3) 1147 (75.7)
Pre-pregnancy body mass index, n (%) Underweight Normal weight Overweight Obese	213 (14.1) 1029 (67.9) 225 (14.9) 48 (3.2)
Family support, n (%), yes	1452 (95.8)
Friends support, n (%), yes	1425 (94.1)
Medical workers support, n (%), yes	1338 (88.3)
Regular exercise before pregnancy, n (%), yes	674 (44.5)
Active or passive smoking before pregnancy, n (%), yes	198 (13.1)
Alcohol drinking before pregnancy, n (%), yes	150 (9.9)
History of spontaneous abortions, n (%), yes	236 (15.6)
Parity, n (%) Primiparous Multiparous	1233 (81.4) 282 (18.6)
Current stage of pregnancy, n (%) First trimester: ≤13+6 weeks Second trimester:14-27+6weeks Third trimester: ≥28 weeks	668 (44.1) 389 (25.7) 458 (30.2)
Singleton pregnancy, n (%), yes	1499 (98.9)
Nausea and vomiting during pregnancy, n (%), yes	1202 (79.3)
Measures taken to prevent miscarriage, n (%), yes	612 (40.4)
Gestational diabetes, n (%), yes	58 (3.8)
Poor prenatal sleep quality, n (%), yes	639 (42.2)
Prenatal anxiety, n (%), yes	114 (7.5)
Prenatal depression, n (%), yes	391 (25.8)

^a One Chinese Yuan (¥) = US $0.1492.

Physical activity levels of the participants

Table 2 describes the PA level overall during pregnancy and according to intensity. The median energy expenditure on total PA was 693 MET min/week. Overall, 129 women did not report any type of PA. Walking as the main form of PA accounted for 92.7% of total MET. The prevalence of physical inactivity was 47.5%, and only 2.8% of women achieved the American College of Obstetricians and Gynecologists PA goal of at least 150 min of moderate-to-vigorous exercise per week. Furthermore, 94.6% of the women who reported sufficient PA did not meet the guideline of more than 150 min of moderate-to vigorous-intensity activity per week (Table 3).

Table 2 Physical activity characteristics of participants (n=1515).

Physical activity

N (%)

Median (IQR) ^b

MET ratio (%) ^c

Energy consumption (MET-min/week) ^a

Total activity

Light-intensity activity (walking)

Moderate-to vigorous-intensity activity

Reported no physical activity

1515 (100.0)

1381 (91.2)

118 (7.8)

129 (8.5)

693 (297, 990)

693 (396, 990)

480 (240, 942)

—

100.0

92.7

7.3

—

Physical inactivity

No

Yes

796 (52.5)

719 (47.5)

—

Meet the guideline

No

Yes

1472 (97.2)

43 (2.8)

—

^aMET: metabolic equivalent.

^bIQR: interquartile range.

^cMET ratio: The contribution of the metabolic equivalent of each intensity of activity to the total physical activity metabolic equivalent.

Table 3 Prevalence of meeting physical activity guidelines in pregnant women who achieved sufficient physical activity (n=1515).

Categories	PA^a＜600 MET min/week (n=719)	PA^a≥600 MET min/week (n=796)
Do not meet the guideline, n (%)	719 (100.0)	753 (94.6)
Meet the guideline, n (%)	0 (0.0)	43 (5.4)

^a PA: physical activity

Factors related to physical inactivity during pregnancy

Table 4 shows the factors associated with physical inactivity in detail. Pregnant women with an individual income of more than 10,000 yuan per month (adjusted OR 0.648, 95% CI 0.505–0.831) were less likely to be physically inactive than those with a lower income. Moreover, regular exercise before conception contributed to maintaining adequate PA during pregnancy (adjusted OR 0.575, 95% CI 0.464–0.711). However, the physical inactivity rate was significantly higher in the first trimester than in the second trimester (adjusted OR 0.534, 95% CI 0.411–0.693) or third trimester (adjusted OR 0.615, 95% CI 0.470–0.806). Women who had nausea and vomiting during pregnancy were 1.307 times more likely to be physically inactive than those who did not have these symptoms (adjusted OR 1.307, 95% CI 1.002–1.705).

Table 4 Binary logistic regression analysis of the factors associated with physical inactivity.

Variables

B

OR ^a

95% CI ^b

P value

Age (years)

＜25

25-29

30-34

≥35

—

0.299

0.359

0.323

1.000

1.348

1.432

1.381

(reference)

0.771–2.358

0.819–2.502

0.750–2.544

—

0.295

0.208

0.300

level of education

High school or less

College

Professional or graduate

—

–0.148

0.024

1.000

0.862

1.024

(reference)

0.570–1.301

0.655–1.594

—

0.481

0.916

Personal monthly income^d

＜¥10,000

≥¥10,000

—

–0.434

1.000

0.648

(reference)

0.505–0.831

—

0.001^c

Regular exercise before pregnancy

Yes

–0.554

0.575

0.464–0.711

＜0.001^c

Alcohol drinking before pregnancy

Yes

0.232

1.261

0.885–1.798

0.199

Pre-pregnancy body mass index

Underweight

Normal weight

Overweight

Obese

—

0.028

–0.294

0.146

1.000

1.029

0.745

1.157

(reference)

0.756–1.399

0.503–1.103

0.603–2.219

—

0.857

0.142

0.661

History of spontaneous abortions

Yes

–0.013

0.930

0.738–1.319

0.930

Current stage of pregnancy

First trimester: ≤13+6 weeks

Second trimester:14-27+6weeks

Third trimester: ≥28 weeks

—

–0.627

–0.485

1.000

0.534

0.615

(reference)

0.411–0.693

0.470–0.806

—

＜0.001^c

Nausea and vomiting during pregnancy

Yes

0.268

1.307

1.002–1.705

0.049^c

Poor prenatal sleep quality

Yes

–0.199

1.220

0.984–1.513

0.069

^aOR: odds ratio.

^b95% CI: 95% confidence interval.

^cP＜0.05.

^dOne Chinese Yuan (¥) = US $0.1492.

This study evaluated physical inactivity and related factors in pregnant women in Shanghai, China. We found that 47.5% of our study participants do not engage in sufficient PA during pregnancy, with an average of only 287.78 MET min/week, which is reasonably consistent with the figure of 44.75% reported for the 15 provinces in China [16]. Use of the same criteria with a total energy expenditure of <600 MET min/week to define physical inactivity may account for these findings. However, the proportion of pregnant women in a study from Serbia [10] who do not have adequate PA was found to be slightly lower despite using the same classification standard, and may reflect a difference in the trimesters studied or a difference in the study populations. In a study that used the Prenatal Physical Activity Questionnaire, 57.1% of pregnant women reached the recommended level (≥150 min of moderate-to-vigorous activity per week) in Chengdu [15], whereas only 11% fulfilled the recommendations during pregnancy (≥2 hours of moderate exercise per week) in Tianjin [11]. Studies from other countries, no matter the developed countries, including the United States, Norway and Ireland [14, 34, 35], the developing countries including Brazil and Vietnam [18, 36], and underdeveloped countries in South Africa [23] consistently reported lower PA levels in pregnant women, despite using different measurement tools and evaluation methods.

In our study, only 2.8% of pregnant women achieved the level of prenatal PA recommended by the international guidelines. In fact, moderate-intensity activity is assigned a MET value of 4 in this investigation, to some extent, the international guidelines of at least 150 min of moderate-to-vigorous activity per week is equivalent to 600 MET min/week. However, more than ninety percent of our study participants who reported sufficient PA of ≥600 MET min/week did not meet the international guidelines. The main reason for such a huge difference between the two results is that walking as low-intensity activity, is the dominant form of PA and accounted for 92.7% of total MET values. Moreover, it has been suggested that some health care workers have conservative views about PA during pregnancy and question the safety of moderate to vigorous PA, which may result in recommendations for lighter PA during pregnancy [37]. Our finding that PA during pregnancy consisted of walking which accounted for a relatively large proportion is similar to studies in Ethiopia and Poland [12, 21]. In our study, walking was assigned a MET value of 3.3 and included in calculating the result of PA level to define sufficient PA. However, walking is excluded from the international guidelines, which focus only on moderate and high-intensity PA. And without a doubt, moderate or vigorous intensity activities can provide substantial health benefits; for example, pregnant women engaged in at least 600 MET min/week of moderate PA (e.g., 140 minutes of brisk walking and stationary cycling) can reduce their risk of GDM or gestational hypertension by at least 25% [38]. Light-intensity activities, such as walking, can have health benefits too, but the greatest benefit often occurs when sedentary behavior is replaced with moderate to-vigorous physical activity [39]. Therefore, we should suggest a gradual increase in the amount and intensity of activity; for example, increasing their walking pace and choosing exercise that is more acceptable, such as brisk walking, to promote the moderate or vigorous PA recommended by the guidelines.

We used a multivariable logistic regression model to identify factors associated with physical inactivity during pregnancy in Shanghai and found that women who had engaged in regular exercise before pregnancy were more likely to have a higher PA level during pregnancy than women who had not, which is consistent with studies from Arba Minch Town in Ethiopia [19], Campinas in Brazil [18], data from the US Centers for Disease Control and Prevention [14] and a study performed in Chengdu in China [15]. This finding indicates that starting exercise before conception may help women to achieve adequate PA during pregnancy and underscores the importance of lifestyle changes before pregnancy. Of note is a prospective study from Spain that found that nearly half of 1,175 pregnant women engaged in sufficient PA before pregnancy but did not maintain their PA level during pregnancy [9]. This may be attributed to physical discomfort during pregnancy, in particular nausea and vomiting [40], which is consistent with our findings, in addition to low back pain, fatigue, fear of injury, and uncertainty about the safety of exercising during pregnancy [41].

In our study, women with higher incomes were less likely to have a low PA level during pregnancy, which is in line with the reports by Galliano et al. and Yu et al. [13, 17]. The study in Serbian women found that inadequate PA during pregnancy was more marked in low-income families, which could reflect a lack of leisure time for exercise [10]. We also found a decrease in the likelihood of physical inactivity as pregnancy advanced from the first trimester to the second and third trimesters. A cross-sectional study of 1077 Chinese pregnant women found that pregnant women in the third trimester were more likely to meet the international guidelines than those in the early stages of pregnancy [15]. Likely explanations for this finding include the traditional Chinese practice of protecting the fetus from miscarriage by rest and physical discomfort, particularly morning sickness. However, as mentioned, the available evidence indicates that interventions to improve the PA level during late pregnancy should be implemented during early pregnancy or even before pregnancy. The cohort study showed that women with adequate PA levels in early pregnancy were more likely to engage in adequate PA in mid-to-late pregnancy [16]. Similarly, Okafor and Goon showed that women who started PA in the first trimester were more active and more likely to meet the guideline than those who started PA in the second trimester [23].

Although individual demographics, PA levels before pregnancy, physiological changes during pregnancy, etc. may affect the ability to engage in PA, there is limited qualitative information in the literature on the causes that affect PA in pregnant women. More qualitative or mix-method studies are needed in the future to improve our understanding of women’s willingness or otherwise to engage in PA during pregnancy and inform interventions in clinical practice.

Limitations

This study had several limitations. First, the PA data were self-reported using the IPAQ, which introduces the possibility of reporting bias. More accurate data on the amount and frequency of PA during pregnancy would be obtained by use of electronic activity monitors, such as wearable bracelets, accelerometers, or pedometers. Second, the study had a cross-sectional design, which meant that we could not obtain information on changes in the PA level as the women moved through the trimesters. Therefore, prospective studies are needed in the future. Third, our study participants were from only one center in Shanghai and may not be representative of the entire city. However, despite these limitations, this study provides useful information concerning physical inactivity during pregnancy in Shanghai that can be used for comparative purposes in future studies.

The prevalence of physical inactivity among pregnant women in China remains high, particularly in women with a lower monthly income, those who have not engaged in regular exercise before pregnancy, and those who experience nausea and vomiting during pregnancy. More effort is needed to help these women overcome barriers to prenatal PA. Furthermore, we need a better understanding of the dynamic changes in PA that occur during pregnancy and how these may be affected by the coronavirus pandemic, which is likely to continue into the future. Further research that includes a combination of quantitative analysis and qualitative methods is needed to obtain more information on how to promote PA during pregnancy.

PA: Physical activity; GDM: Gestational diabetes mellitus; WHO: World Health Organization; ACOG: American College of Obstetricians and Gynecologists; SOGC: Society of Obstetricians and Gynecologists of Canada; CSEP: Canadian Society for Exercise Physiology; IPAQ: International Physical Activity Questionnaire; MET: Metabolic equivalent; IPAQ-SF: International Physical Activity Questionnaire short form; TEE: Total energy expenditure; BMI: Body mass index; PSQI: Pittsburgh Sleep Quality Index; ORs: Odds ratios; CIs: Confidence intervals; IQR: interquartile range.

Ethics approval and consent for participation in research

The study protocol approved by the Institutional Review Board of the Research Committee of the Obstetrics and Gynecology of Hospital Fudan University (protocol code 202123). All methods were performed in accordance with the relevant guidelines and regulations of the Declaration of Helsinki and all participants provided written informed consent to participate in the study prior to data collection.

Consent for publication

Not applicable.

Competing interests

There is no conflict of interest.

Availability of data and materials

The data that support the findings of this study can be obtained by contacting the corresponding author Na Wang, upon reasonable request.

Funding

This research was supported by the Shanghai Municipal Health Commission [grant number: 202150050]; the Obstetrics and Gynecology Hospital of Fudan University [grant number: FC2021CR203_ZC].

Author Contributions

Na Wang and Yan Ding conceived and designed the study. Yuping Lin, Xiaoxia Ma and Feng Xu analyzed and interpreted the data. Tianchun Zhou drafted the manuscript. Na Wang reviewed and edited the paper. All authors have read and agreed to the published version of the manuscript.

Acknowledgements

We want to thank all the pregnant women who participated in our study and the collaborating hospital for supporting this project. We acknowledge the contributions of the students, doctor Weihong Hu, nursing administrators Beibei Shen and Xinli Zhu, etc. from the collaborating hospital for their helps in recruiting the participants.

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No competing interests reported.

Factors influencing physical inactivity status among Chinese pregnant women: a cross-sectional study

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Version 1

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Version 1